Spigit Prediction Markets

Recently, IBM launched the SmarterCities Predictive Idea Markets, powered by Spigit. The markets are set up to poll crowd sentiment on different, non-exclusive outcomes to major questions facing cities over the next 40 years.

As has been pointed out here, here and here, the SmarterCities site is not a prediction market at all. It is an “opinion market” in which a variety of participants invest in multiple approaches based on their view of effectiveness of those approaches. They do not have mutually exclusive outcomes, nor can the different outcomes be verified as occurring when the markets close. Consider the site as an initiative in assessing people’s sentiment on different options related to the future infrastructure needs of cities.

Companies such as InTrade and BetFair operate prediction markets as central destinations where people participate in different markets. Spigit provides prediction markets for companies to use for their own purposes, whether internally for employees or externally for participants. As such, it ultimately is up to each client to decide how they will use Spigit’s technology.

Spigit offers two types of prediction markets:

• Traditional markets based on the stock market paradigm
• Token investment-based market

With that as background, presented below is a description of Spigit’s stock market form of prediction markets.

Basic Prediction Market Set-up

The intent of Spigit prediction markets is to make it easy to set one up and get going quickly. Below is a screenshot for setting up a prediction market on the Spigit platform.

Prediction market question, close date and description: The market starts with the question posed to participants. The standard advice to companies using the prediction market service is to create a “question that can be definitively answered within the set timeframe.”

Close date is when the market closes, and should relate to when the answer to a question can be definitively known.

The platform allows additional description to be provided for a question. This can include information such as the definitive source of record for defining which outcome occurs.

Create possible outcomes: The prediction market will have several possible outcomes. Keys in selecting outcomes include:

• Each outcome is mutually exclusive from the others. Only one of the outcomes will be realized upon closing of the market.
• The outcomes provided should cover 100% of all possibilities. This means that one of the outcomes will be realized upon the closing date.

Initial prices: In addition to listing the outcomes, the maker of a prediction market also sets the initial probabilities for each outcome. These probabilities take the form of prices in the prediction market. For many prediction markets, setting the initial probabilities as equal for all outcomes makes sense. All outcomes may be truly equally possible, or the market administrator is fine with letting probabilities naturally find their own level by participants’ actions.

Alternatively, different initial probabilities may be set for the different outcomes. This is useful in situations where financial rewards are part of the market. If a particular outcome is known to have a higher probability of occurrence, setting the initial probability higher can reduce the financial reward if that outcome does indeed occur.

Prediction Market Mechanics

Once the prediction market is live, participants will be able to buy and sell positions in different outcomes. Participants start with a given amount of currency. They are then free to trade different outcomes in the prediction market, based on their own views and sources of information.

Each participant will be presented with a list of outcomes, and their initial probabilities of occurrence:

From this page, each participant can make trades on the different outcomes by clicking the “buy/sell” button. The screenshot below shows a trading page for the outcome “9.4 – 9.5”, where participants can buy and sell positions in a fictional currency dooklas:

Buying and selling: Participants buy shares of an outcome when they believe it has a reasonable chance of occurring. If their view is that the probability of an outcome exceeds the current market probability, they may buy as well. Participants sell positions when their view of the outcome changes, or they believe an outcome has a lower probability than what the market is showing. Sales are only for positions already held by a participant.

Updating probabilities: The probabilities of each outcome are affected by the trades in the prediction market. The bigger the trade, the more it affects the probability of the outcome, up or down. In addition, because the probability of all outcomes must equal 100%, the probabilities of all other outcomes are affected by the trade. Assume a participant buys 100 shares of the “9.4 – 9.5” outcome. The share price is higher than the initial price of 17.000, going for 19.008 dooklas. After making the purchase, all probabilities adjust, as shown below:

Spigit allows prediction market administrators to plug in different pricing functions including the most popular logarithmic function in use by a number of other prediction market vendors. The platform market maker uses the algorithm to adjust the probabilities after a trade.

In this way, the market stays up-to-date with the latest probabilities as represented by the participants’ collective view.

Alerts: As the prices (probabilities) of each outcome change, participants can elect to receive alerts. These alerts can be set for when the probabilities drop below or above specified thresholds.

Leaderboard: Participants’ currency positions are maintained by the Spigit platform. The Leaderboard shows the top participants based on their net worth. Net worth changes as prediction markets are closed out, and winners and losers are determined.

Choose a winner: Once the outcome is known on the defined date, and the market closes, the prediction market administrator chooses the winning outcome. All holders of shares for that outcome are paid out at a price of 100.000. Gains are based on the different share prices purchased in the winning outcome. Share prices of other outcomes go to zero, becoming worthless.

Prediction Market Use Cases

Several companies are using or will be deploying Spigit prediction markets for various purposes. The table below shows these:

Spigit prediction market - enterprise use cases

You can contact Spigit to learn more.